Why did the paper focus on common trends across each component rather than a single overarching classification of CMC models? The study of common trends in modeling, rather than a single overarching classification, helped in providing a multi-faceted view of CMC that can generalize on future models, and identify possible open-ended research questions, such as (a) For history selection, HAM [1]} has proved to be both effective and intuitive in selecting relevant history turns. The application of this history selection approach on previous techniques that considered immediate K turns could be experimented with. (b) As mentioned in training methodology (section REF ), RoBERTa-based CMC model [2]} that used knowledge distillation and adversarial training achieved state-of-the-art CoQA results [3]}. This suggests that different training approach along with multi-task learning improves the performance of base models. These procedures could be experimented with more advanced models such as HAM [1]} and FlowDelta [5]}.
